小波阈值去噪法在MEMS陀螺信号处理中的应用

近年来MEMS陀螺发展迅速，应用广泛，但性能参差不齐。为改善MEMS陀螺的输出信号性能，综述了近年来小波阈值去噪法在该领域内的研究进展情况。重点从阈值函数的不同改进形式、阈值选取方式的不同以及分解层数三方面对比分析各小波阈值去噪法之间的优缺点。通过现阶段的去噪效果评判标准，结合MEMS陀螺信号的特点，对近年来小波阈值去噪的应用情况进行分析说明，总结小波阈值去噪法在不同使用条件下对MEMS陀螺信号处理上的优势与不足，为后续相关研究提供一定的参考价值。     

Transfer learning: A new aerodynamic force identification network based on adaptive EMD and soft thresholding in hypersonic wind tunnel

The aerodynamic test in the pulse combustion wind tunnel is very important for the design, evaluation and optimization of aerodynamic characteristics of the hypersonic aircraft. The test accuracy even affects the success or failure of hypersonic aircraft development. In the aerodynamic test of pulse combustion wind tunnel, the aerodynamic signal is disturbed by the inertial force signal, which seriously affects the test accuracy of aerodynamic force. Aiming at the above problems, this paper innovatively proposes an aerodynamic intelligent identification method, that is the transfer learning network based on adaptive Empirical Modal Decomposition (EMD) and Soft Thresholding (TLN-AE&ST). Compared with the existing aerodynamic intelligent identification model based on deep learning technology, this study introduces the transfer learning idea into the aerodynamic intelligent identification model for the first time. The TLN-AE&ST effectively alleviates the problem of scarcity of training samples for intelligent models due to the high cost of wind tunnel tests, and provides a new idea for further implementation of deep learning technology in the field of wind tunnel aerodynamic testing. And this study designed residual attention block with soft threshold and dense block with adaptive EMD in TLN-AE&ST model. Residual attention block with soft threshold module can more effectively suppress the influence of instrument noise signal on model training effect. Dense block with adaptive EMD makes the deep learning model no longer a black box to a certain extent, and has certain physical significance. Finally, a series of wind tunnel tests were carried out in the Φ = 2.4 m pulse combustion wind tunnel of China Aerodynamic Research and Development Center to verify the effectiveness of TLN-AE&ST.     

电源端口电磁脉冲防护方法研究

为了解决电源端口在不同电磁脉冲条件下的防护问题，提出了一种适用于多种电磁脉冲防护设计方 法。该方法能依据不同电磁脉冲波形精准指导防护电路设计；该方法使用CST 对电源端口电源线及电路建模 进行仿真分析；利用其电磁仿真结果，设计防护电路；并采用数值计算方法对防护电路中的防护器件瞬态电压 抑制器进行精准设计，可保证瞬态电压抑制器本身及后级电路不发生损坏，可为电源端口防护不同电磁脉冲提 供理论依据。     

光谱01卫星脉冲等离子推力器电源处理单元的开发

针对光谱01卫星应用需求，提出了脉冲等离子推力器电源处理单元的设计方案，给出了验证结果。采用反激变换拓扑和恒功率方式实现了以2.5Hz的频率将5.76μF的储能电容器充电至1600V，将0.68μF的火花塞点火电容充电至800V；采用超快恢复高压整流管、高压绕组串联、高压整流管串联和开关频率设计解决了反激变换器整流二极管反向恢复引起的功率反向传输问题；采用输出钳位二极管和限流电阻解决了储能电容振荡负电压反向一次母线充电的问题。PPT的地面寿命试验和在轨测试结果表明，所设计的电源处理单元方案合理可行。     

基于固定阈值事件触发扩张状态观测器的多智能体协同目标环绕控制

针对复杂多扰环境下面向未知运动目标的多智能体对峙跟踪问题,提出了一种基于固定阈值事件触发扩张状态观测器(FTESO)的多智能体协同目标环绕控制方法。首先,建立了智能体与目标的相对运动模型,将目标加速度、模型非线性、环境摄动视为集总干扰,利用量测的相对位置信息构造可降低测量端状态更新频次的FTESO,以实现在非周期采样条件下对于相对速度不可测和集总干扰未知的精准估计。其次,结合速度方向场理论生成目标与智能体间的期望相对速度,根据相邻智能体间的相对角间距信息与FTESO的观测结果,设计了一种不依赖目标加速度信息的多智能体相位协同一致性协议,使得多智能体能够以指定环绕半径、环绕角速度和相对角间距实现对未知运动目标的环绕跟踪。借助Lyapunov稳定性理论,证明了闭环系统中所有误差信号最终一致有界。最后,通过仿真和比较结果验证了所提算法的有效性。